Penerapan Teknologi Deep Learning untuk Meningkatkan Keterampilan Membaca Siswa SMP Melalui Aplikasi Berbasis AI - Basuki Basuki; Murhadi Murhadi; Andrian Nuriza Johan; Nurhidayati Nurhidayati; Joko Purwanto; Ari Fajar Isbakhi; Maryuli Setyoko (JURNAL RISET RUMPUN ILMU PENDIDIKAN, 2026)
This study aims to develop and implement an artificial intelligence-based reading learning application using Deep Learning technology to enhance the literacy skills of eighth-grade junior high school students. The research employed the Kemmis & McTaggart Classroom Action Research model combined with a mixed-methods approach. Data collection involved pretests and posttests, complemented by observations, interviews, and questionnaires. The findings revealed that the use of this application significantly improved students' reading comprehension, question-answering skills, and overall engagement in the learning process. Key features of the application, such as adaptive learning technology, allowed for real-time adjustments to the difficulty level of the material, which catered to each student’s individual learning pace. Additionally, the provision of instant feedback enhanced the learning experience by helping students understand their progress and areas for improvement. These results suggest that the application is an effective tool in fostering literacy development and aligns with the goals of the Independent Curriculum. Consequently, this Deep Learning-based application offers a promising innovation for improving student literacy skills in the digital age.